mica-mni / micaopen Goto Github PK

Hello! I'd like to replicate what was done in the 2019 paper and generate the MPC matrix from BigBrain data. I'm confused about the data organization, however, since there seems to be a discrepancy between what the scripts need and what the data folder in the repo looks like.

Is the data in the repo preprocessed? What is a subject list (for script 1) supposed to look like? What's the input data to these scripts generally supposed to look like?

Thank you!

I am interested in testing the model from the recent publication on prediction of functional connectivity from the structural connectome. I set up a Singularity image based on the Python 3.8 image with the dependencies listed in this repo, but I run into this error when trying to import the function as suggested:

>>> from utils import run_sf_prediction
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/micaopen/sf_prediction/utils.py", line 10, in <module>
    from pymanopt.manifolds import Rotations
ImportError: cannot import name 'Rotations' from 'pymanopt.manifolds' (/usr/local/lib/python3.8/site-packages/pymanopt/manifolds/__init__.py)

Is there a specific version of pymanopt that is required to run this code?
Any help would be greatly appreciated!